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Oriol Pujol; Debora Gil; Petia Radeva |
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Title |
Fundamentals of Stop and Go active models |
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Journal Article |
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Year |
2005 |
Publication |
Image and Vision Computing |
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23 |
Issue |
8 |
Pages |
681-691 |
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Keywords |
Deformable models; Geodesic snakes; Region-based segmentation |
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Abstract |
An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation. |
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Butterworth-Heinemann |
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Newton, MA, USA |
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0262-8856 |
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IAM;MILAB;HuPBA |
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Call Number |
IAM @ iam @ PGR2005 |
Serial |
1629 |
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Author |
Oriol Pujol; David Masip |
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Title |
Geometry-Based Ensembles: Toward a Structural Characterization of the Classification Boundary |
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Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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31 |
Issue |
6 |
Pages |
1140–1146 |
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This article introduces a novel binary discriminative learning technique based on the approximation of the non-linear decision boundary by a piece-wise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points – points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and non-linear behavior is obtained. The simplicity of the method allows its extension to cope with some of nowadays machine learning challenges, such as online learning, large scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database. Finally, we apply our technique in online and large scale scenarios, and in six real life computer vision and pattern recognition problems: gender recognition, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease severity detection, clef classification and action recognition using a 3D accelerometer data. The results are promising and this paper opens a line of research that deserves further attention |
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OR;HuPBA;MV |
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BCNPCL @ bcnpcl @ PuM2009 |
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1252 |
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Author |
O. Rodriguez; J. Mauri; E Fernandez-Nofrerias; A. Tovar; R. Villuendas; V. Valle; Oriol Pujol; Petia Radeva |
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Title |
Analisis de texturas mediante la modificacion de un modelo binario local para la segmentacion automatica de secuencias de ecografia intracoronaria |
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Year |
2003 |
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Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares |
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Sevilla (Spain) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RMF2003f |
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413 |
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Author |
O. Rodriguez-Leor; E Fernandez-Nofrerias; J. Mauri; C. Garcia; R. Villuendas; V. Valle; Oriol Pujol; Petia Radeva |
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Title |
Intravascular ultrasound segmentation using local binary patterns |
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2003 |
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European Heart Journal (IF: 5.997), ESC Congress 2003 |
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Vienna (Austria) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RFM2003a |
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407 |
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O. Rodriguez-Leor; Carlo Gatta; E Fernandez-Nofrerias; Oriol Pujol; Neus Salvatella; C. Bosch; H. Tizon; Petia Radeva; J. Mauri |
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Title |
Computationally Efficient Image-based IVUS Pullbacks Gating |
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2008 |
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European Heart Journal, ESC Supplement, Munich, 2008, p. 775 |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RGF2008 |
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1036 |
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